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Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128)

OBJECTIVES: Ulnar collateral ligament (UCL) injury is a significant concern in elite throwers, and it is associated with prolonged time away from competition in Major League Baseball (MLB) pitchers. Identifying athletes at higher risk of injury, with the subsequent goal of injury prevention, may pos...

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Autores principales: Fury, Matthew, Scarborough, Donna, Oh, Luke, Wright-Chisem, Joshua, Fury, Jacob, Berkson, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562607/
http://dx.doi.org/10.1177/2325967121S00271
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author Fury, Matthew
Scarborough, Donna
Oh, Luke
Wright-Chisem, Joshua
Fury, Jacob
Berkson, Eric
author_facet Fury, Matthew
Scarborough, Donna
Oh, Luke
Wright-Chisem, Joshua
Fury, Jacob
Berkson, Eric
author_sort Fury, Matthew
collection PubMed
description OBJECTIVES: Ulnar collateral ligament (UCL) injury is a significant concern in elite throwers, and it is associated with prolonged time away from competition in Major League Baseball (MLB) pitchers. Identifying athletes at higher risk of injury, with the subsequent goal of injury prevention, may positively impact pitcher health while mitigating the significant economic impact of this injury on professional organizations. As technology continues to advance, more granular assessments of performance are becoming possible. In 2015, Major League Baseball introduced StatCast, a spatiotemporal data tracking system that uses a standardized camera system and radar technology, to optically track player and ball movement to measure and quantify game events. This technology allows for further investigation of the science of pitching and provides new frontiers for injury research. Understanding UCL injuries in MLB pitchers may also provide insight into youth pitching injuries. To date, there is a paucity of evidence regarding risk factors of UCL injury in MLB pitchers. METHODS: All MLB pitchers who underwent primary UCLR between 2015 and 2019 were identified from publicly available reports. This date range was selected to capture the seasons in which Statcast data was available. Advanced analytics and pitch metrics from the injury season—including velocity, spin rates, and pitch movement from MLB StatCast data—were collected as well as the seasonal data of an uninjured control group. Binomial logistic regression analysis was performed to determine risk factors for UCL injury. RESULTS: Seventy-six MLB pitchers undergoing primary UCL reconstruction were included, and a control group of 95 uninjured pitchers was identified. There was no significant difference in age, height, weight, or BMI between the two cohorts. A logistic regression model was created using the following variables: 4-seam fastball velocity, 4-seam fastball spin rate, slider spin rate, curveball spin rate, strikeout percentage, and wins above replacement (WAR). The model explained 18.4% of the variance and predicted 70.4% of UCL injuries. Increasing WAR was associated with increasing likelihood of subsequent UCL injury (odds ratio [OR] 2.34; 95% CI, 1.08–5.07; p = 0.031). CONCLUSIONS: When controlling for fastball velocity and pitch spin rates, MLB pitchers who are more valuable, as indicated by WAR, may be at an elevated risk of UCL injury. While velocity is a known risk factor for UCL injury, this model indicates that other factors, including performance or pitch metrics, may influence single-season injury risk and warrant future investigation in multi-year studies.
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spelling pubmed-85626072021-11-04 Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128) Fury, Matthew Scarborough, Donna Oh, Luke Wright-Chisem, Joshua Fury, Jacob Berkson, Eric Orthop J Sports Med Article OBJECTIVES: Ulnar collateral ligament (UCL) injury is a significant concern in elite throwers, and it is associated with prolonged time away from competition in Major League Baseball (MLB) pitchers. Identifying athletes at higher risk of injury, with the subsequent goal of injury prevention, may positively impact pitcher health while mitigating the significant economic impact of this injury on professional organizations. As technology continues to advance, more granular assessments of performance are becoming possible. In 2015, Major League Baseball introduced StatCast, a spatiotemporal data tracking system that uses a standardized camera system and radar technology, to optically track player and ball movement to measure and quantify game events. This technology allows for further investigation of the science of pitching and provides new frontiers for injury research. Understanding UCL injuries in MLB pitchers may also provide insight into youth pitching injuries. To date, there is a paucity of evidence regarding risk factors of UCL injury in MLB pitchers. METHODS: All MLB pitchers who underwent primary UCLR between 2015 and 2019 were identified from publicly available reports. This date range was selected to capture the seasons in which Statcast data was available. Advanced analytics and pitch metrics from the injury season—including velocity, spin rates, and pitch movement from MLB StatCast data—were collected as well as the seasonal data of an uninjured control group. Binomial logistic regression analysis was performed to determine risk factors for UCL injury. RESULTS: Seventy-six MLB pitchers undergoing primary UCL reconstruction were included, and a control group of 95 uninjured pitchers was identified. There was no significant difference in age, height, weight, or BMI between the two cohorts. A logistic regression model was created using the following variables: 4-seam fastball velocity, 4-seam fastball spin rate, slider spin rate, curveball spin rate, strikeout percentage, and wins above replacement (WAR). The model explained 18.4% of the variance and predicted 70.4% of UCL injuries. Increasing WAR was associated with increasing likelihood of subsequent UCL injury (odds ratio [OR] 2.34; 95% CI, 1.08–5.07; p = 0.031). CONCLUSIONS: When controlling for fastball velocity and pitch spin rates, MLB pitchers who are more valuable, as indicated by WAR, may be at an elevated risk of UCL injury. While velocity is a known risk factor for UCL injury, this model indicates that other factors, including performance or pitch metrics, may influence single-season injury risk and warrant future investigation in multi-year studies. SAGE Publications 2021-10-29 /pmc/articles/PMC8562607/ http://dx.doi.org/10.1177/2325967121S00271 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc-nd/4.0/This open-access article is published and distributed under the Creative Commons Attribution - NonCommercial - No Derivatives License (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits the noncommercial use, distribution, and reproduction of the article in any medium, provided the original author and source are credited. You may not alter, transform, or build upon this article without the permission of the Author(s). For article reuse guidelines, please visit SAGE’s website at http://www.sagepub.com/journals-permissions.
spellingShingle Article
Fury, Matthew
Scarborough, Donna
Oh, Luke
Wright-Chisem, Joshua
Fury, Jacob
Berkson, Eric
Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128)
title Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128)
title_full Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128)
title_fullStr Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128)
title_full_unstemmed Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128)
title_short Performance Analytics and Pitch Metrics as Predictors of Ulnar Collateral Ligament Injury in Major League Baseball Pitchers (128)
title_sort performance analytics and pitch metrics as predictors of ulnar collateral ligament injury in major league baseball pitchers (128)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562607/
http://dx.doi.org/10.1177/2325967121S00271
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